Subsidence Monitoring Base on SBAS-InSAR and Slope Stability Analysis Method for Damage Analysis in Mountainous Mining Subsidence Regions

Abstract

Surface subsidence caused by coal mining has a great impact on the geological and ecological environments and causes damage to houses, roads, and industrial buildings. In order to understand the subsidence pattern in the mountainous mining regions, three mining faces of the Zhangjiamao mining area in the north of Shaanxi province, northwestern China are taken as case study. Firstly, the small baseline subset (SBAS) technology is used to process 12 images obtained in the mining area to investigate the subsidence data from December 2019 to April 2020. The boundary of surface deformation of the mining area interpreted by the SBAS-InSAR technology is inconsistent with the theoretical boundary suggested by coal mine subsidence theories. Especially, there are some areas in which the real subsidence are larger than estimated area. This discrepancy must be corrected as steep slopes near the theoretical boundary may increase the likelihood of landslides. Our research indicates that: (1) The accumulated displacement and the maximum deformation rate reached −120.759 mm and −270.012 mm/yr in the study area, and the subsidence boundary of the three mining faces is revealed; (2) the combination of the predicted boundary and slope stability analysis can effectively identify the landslide region at the edge of subsidence boundary; (3) the field surveys have proved the effectiveness of this method. The mining area subsidence revealed by our research helps to further understand the impact of land subsidence caused by mining in the mountainous areas and provides a practical method to predict subsidence boundaries and the likelihood for landslides.

Integrated PSInSAR and GNSS for 3D Displacement in the Wudongde Area

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A New Method for Continuous Track Monitoring in Regions of Differential Land Subsidence Rate Using the Integration of PS-InSAR and SBAS-InSAR

“…The input parameters are described in Table 2. Due to the high temporal and spatial sampling rate, SBAS-InSAR requires few satellite images, but generally, more than eight images, to ensure monitoring accuracy [6,48]. The fast-rate region can be searched for by applying SBAS-InSAR to small SAR data sets, including partial time-series SAR data and new SAR data from strongly developed ground deformation areas.…”

TDFPI: A Three-Dimensional and Full Parameter Inversion Model and Its Application for Building Damage Assessment in Guotun Coal Mining Areas, Shandong, China

“…Declercq investigated the post-mining ground deformations and their transition following the closure of coal mines in Belgium by utilizing three decades of MT-InSAR [13]. These studies demonstrated that InSAR techniques can overcome the limitation of point-wise traditional geodetic measurement and are capable of detecting large-scale deformation fields with theoretical accuracy reaching the millimeter level [14].…”